Artificial intelligence-enabled electrocardiogram for mortality and cardiovascular risk estimation: a model development and validation study.

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Bibliographic Details
Title: Artificial intelligence-enabled electrocardiogram for mortality and cardiovascular risk estimation: a model development and validation study.
Authors: Sau A; National Heart and Lung Institute, Imperial College London, London, UK; Department of Cardiology, Imperial College Healthcare NHS Trust, London, UK., Pastika L; National Heart and Lung Institute, Imperial College London, London, UK., Sieliwonczyk E; National Heart and Lung Institute, Imperial College London, London, UK; MRC Laboratory of Medical Sciences, Imperial College London, London, UK; University of Antwerp and Antwerp University Hospital, Antwerp, Belgium., Patlatzoglou K; National Heart and Lung Institute, Imperial College London, London, UK., Ribeiro AH; Department of Information Technology, Uppsala University, Uppsala, Sweden., McGurk KA; National Heart and Lung Institute, Imperial College London, London, UK; MRC Laboratory of Medical Sciences, Imperial College London, London, UK., Zeidaabadi B; National Heart and Lung Institute, Imperial College London, London, UK., Zhang H; National Heart and Lung Institute, Imperial College London, London, UK., Macierzanka K; National Heart and Lung Institute, Imperial College London, London, UK., Mandic D; Department of Electrical and Electronic Engineering, Imperial College London, London, UK., Sabino E; Department of Infectious Diseases, School of Medicine and Institute of Tropical Medicine, University of São Paulo, São Paulo, Brazil., Giatti L; Department of Infectious Diseases, School of Medicine and Institute of Tropical Medicine, University of São Paulo, São Paulo, Brazil., Barreto SM; Department of Preventive Medicine, School of Medicine, and Hospital das Clínicas/EBSERH, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil., Camelo LDV; Department of Preventive Medicine, School of Medicine, and Hospital das Clínicas/EBSERH, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil., Tzoulaki I; Systems Biology, Biomedical Research Foundation, Academy of Athens, Athens, Greece; Department of Biostatistics and Epidemiology, School of Public Health, Imperial College London, London, UK., O'Regan DP; MRC Laboratory of Medical Sciences, Imperial College London, London, UK., Peters NS; National Heart and Lung Institute, Imperial College London, London, UK; Department of Cardiology, Imperial College Healthcare NHS Trust, London, UK., Ware JS; National Heart and Lung Institute, Imperial College London, London, UK; MRC Laboratory of Medical Sciences, Imperial College London, London, UK., Ribeiro ALP; Department of Internal Medicine, Faculdade de Medicina, and Telehealth Center and Cardiology Service, Hospital das Clínicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil., Kramer DB; National Heart and Lung Institute, Imperial College London, London, UK; Richard A and Susan F Smith Center for Outcomes Research in Cardiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA., Waks JW; Harvard-Thorndike Electrophysiology Institute, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA., Ng FS; National Heart and Lung Institute, Imperial College London, London, UK; Department of Cardiology, Imperial College Healthcare NHS Trust, London, UK; Department of Cardiology, Chelsea and Westminster Hospital NHS Foundation Trust, London, UK. Electronic address: f.ng@imperial.ac.uk.
Source: The Lancet. Digital health [Lancet Digit Health] 2024 Nov; Vol. 6 (11), pp. e791-e802.
Publication Type: Journal Article; Validation Study; Research Support, Non-U.S. Gov't
Journal Info: Publisher: Elsevier Ltd Country of Publication: England NLM ID: 101751302 Publication Model: Print Cited Medium: Internet ISSN: 2589-7500 (Electronic) Linking ISSN: 25897500 NLM ISO Abbreviation: Lancet Digit Health Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:2589-7500
DOI:10.1016/S2589-7500(24)00172-9